Capacity Coaching: A Focused Ethnographic Evaluation in Clinical Practice

Predictive Modeling for Adverse Events and Risk Stratification Programs for People Receiving Cancer Treatment

Emergency department visits and hospitalizations are common among people receiving cancer treatment, accounting for a large proportion of spending in oncology care and negatively affecting quality of life. As oncology care shifts toward value- and quality-based payment models, there is a need to develop interventions that can prevent these costly and low-value events among people receiving cancer treatment. Risk stratification programs have the potential to address this need and optimally would consist of three components: (1) a risk stratification algorithm that accurately identifies patients with modifiable risk(s), (2) intervention(s) that successfully reduce this risk, and (3) the ability to implement the risk algorithm and intervention(s) in an adaptable and sustainable way. Predictive modeling is a common method of risk stratification, and although a number of predictive models have been developed for use in oncology care, they have rarely been tested alongside corresponding interventions or developed with implementation in clinical practice as an explicit consideration. In this article, we review the available published predictive models for treatment-related toxicity or acute care events among people receiving cancer treatment and highlight challenges faced when attempting to use these models in practice. To move the field of risk-stratified oncology care forward, we argue that it is critical to evaluate predictive models alongside targeted interventions that address modifiable risks and to demonstrate that these two key components can be implemented within clinical practice to avoid unplanned acute care events among people receiving cancer treatment.

Do patients with high versus low treatment and illness burden have different needs? A mixed-methods study of patients living on dialysis

BACKGROUND

Approximately 750,000 people in the U.S. live with end-stage kidney disease (ESKD); the majority receive dialysis. Despite the importance of adherence to dialysis, it remains suboptimal, and one contributor may be patients' insufficient capacity to cope with their treatment and illness burden. However, it is unclear what, if any, differences exist between patients reporting high versus low treatment and illness burden.

METHODS

We sought to understand these differences using a mixed methods, explanatory sequential design. We enrolled adult patients receiving dialysis, including in-center hemodialysis, home hemodialysis, and peritoneal dialysis. Descriptive patient characteristics were collected. Participants' treatment and illness burden was measured using the Illness Intrusiveness Scale (IIS). Participants scoring in the highest quartile were defined as having high burden, and participants scoring in the lowest quartile as having low burden. Participants in both quartiles were invited to participate in interviews and observations.

RESULTS

Quantitatively, participants in the high burden group were significantly younger (mean = 48.4 years vs. 68.6 years respectively, p = <0.001). No other quantitative differences were observed. Qualitatively, we found differences in patient self-management practices, such as the high burden group having difficulty establishing a new rhythm of life to cope with dialysis, greater disruption in social roles and self-perception, fewer appraisal focused coping strategies, more difficulty maintaining social networks, and more negatively portrayed experiences early in their dialysis journey.

CONCLUSIONS AND RELEVANCE

Patients on dialysis reporting the greatest illness and treatment burden have difficulties that their low-burden counterparts do not report, which may be amenable to intervention.

Deriving and validating a brief measure of treatment burden to assess person-centered healthcare quality in primary care: a multi-method study

BACKGROUND

In primary care there is a need for more quality measures of person-centered outcomes, especially ones applicable to patients with multiple chronic conditions (MCCs). The aim of this study was to derive and validate a short-form version of the Patient Experience with Treatment and Self-management (PETS), an established measure of treatment burden, to help fill the gap in quality measurement.

METHODS

Patient interviews (30) and provider surveys (30) were used to winnow items from the PETS (60 items) to a subset targeting person-centered care quality. Results were reviewed by a panel of healthcare providers and health-services researchers who finalized a pilot version. The Brief PETS was tested in surveys of 200 clinic and 200 community-dwelling MCC patients. Surveys containing the Brief PETS and additional measures (e.g., health status, medication adherence, quality of care, demographics) were administered at baseline and follow-up. Correlations and t-tests were used to assess validity, including responsiveness to change of the Brief PETS. Effect sizes (ES) were calculated on mean differences.

RESULTS

Winnowing and panel review resulted in a 34-item Brief PETS pilot measure that was tested in the combined sample of 400 (mean age = 57.9 years, 50% female, 48% white, median number of conditions = 5). Reliability of most scales was acceptable (alpha > 0.70). Brief PETS scores were associated with age, income, health status, and quality of chronic illness care at baseline (P < .05; rho magnitude range: 0.16-0.66). Furthermore, Brief PETS scores differentiated groups based on marital and education status, presence/absence of a self-management routine, and optimal/suboptimal medication adherence (P < .05; ES range: 0.25-1.00). Declines in patient-reported physical or mental health status over time were associated with worsening PETS burden scores, while improvements were associated with improving PETS burden scores (P < .05; ES range: 0.04-0.44). Among clinic patients, 91% were willing to complete the Brief PETS as part of their clinic visits.

CONCLUSIONS

The Brief PETS (final version: 32 items) is a reliable and valid tool for assessing person-centered care quality related to treatment burden. It holds promise as a means of giving voice to patient concerns about the complexity of disease management.